Comments, observations and thoughts from two left coast bloggers on applied statistics, higher education and epidemiology. Joseph is a new assistant professor. Mark is a marketing statistician and former math teacher.

Monday, October 13, 2014

I've got at least two pieces I'd like write around this: one discussing the way we approach AI research (and the innate limitations in that favored approach); the other a rant about how ddulite journalists fail to catch the important subtleties in technology.

I'm sure there are more angles here so I'll throw this one out to the room. What are the examples of a slight change taking a problem from easy to nearly impossible?

2 comments:

I've recently shared this cartoon with some of my developer colleagues who are having to deal with processing large amounts of text to develop algorithms for identifying spelling rules in language. It's very easy to encode any individual rule but in combination, it becomes a very difficult problem indeed. But ultimately solvable up to a point. The moment you try to add any level of sophistication by including grammatical analysis, you're almost completely sunk. But even that is ultimately tractable. It's when it comes to identifying the author's intentions (e.g. deliberate misspellings to reflect the origin of the speaker or to teach a lesson to the reader) that the task becomes impossible.

But an even more straightforward example is speech recognition. I always get asked by people who've done a bit of dictation and are impressed by the results, why we spend so much money on transcription. Why don't we just feed recordings into a speech recognition engine. Yet, all it takes is to have a look at YouTube's automatic captions to see how hopeless this is. Yet, the engine is almost flawless at matching transcriptions to the speech.

The same goes for machine translation.Google translate can rely on its database for any one phrase or simple clause but it fails spectacularly to even convey the gist of a complex newspaper story accurately (e.g. did the Prime minister criticize the Mayor or praise him?). It is quite likely that both machine translation and speech recognition will not progress much further. They can use tricks to mimic higher rate of success but will break on anything resembling human messiness.